Towards AI

MARCH 1, 2023

The technology behind GitHub’s new code search This post provides a high-level explanation of the inner workings of GitHub’s new code search and offers a glimpse into the system architecture and technical underpinnings of the product.

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Google Research AI blog

FEBRUARY 14, 2023

We’re also progressing towards making our learning algorithms more data efficient so that we’re not relying only on scaling data collection. Further improvements are gained by utilizing a novel structured dynamical systems architecture and combining RL with trajectory optimization , supported by novel solvers.

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Heartbeat

JANUARY 9, 2024

This is brought on by various developments, such as the availability of data, the creation of more potent computer resources, and the development of machine learning algorithms. Deployment : The adapted LLM is integrated into this stage's planned application or system architecture.

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ODSC - Open Data Science

JULY 18, 2023

The way Tabnine works is that it uses deep learning algorithms to provide intelligent code suggestions as developers write code. This works by utilizing machine learning algorithms to analyze code patterns and detect bugs, security vulnerabilities, and dreaded code smell. DeepCode is fast becoming a popular debugging tool of choice.

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IBM Journey to AI blog

JULY 18, 2024

The algorithms that empower AI and ML require large volumes of training data, in addition to strong and steady amounts of processing power. Computing Computing is being dominated by major revolutions in artificial intelligence (AI) and machine learning (ML). Distributed computing supplies both.

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The MLOps Blog

MARCH 12, 2024

Optimization: Use database optimizations like approximate nearest neighbor ( ANN ) search algorithms to balance speed and accuracy in retrieval tasks. Caption : RAG system architecture.

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AWS Machine Learning Blog

AUGUST 15, 2023

System complexity – The architecture complexity requires investments in MLOps to ensure the ML inference process scales efficiently to meet the growing content submission traffic. With the high accuracy of Amazon Rekognition, the team has been able to automate more decisions, save costs, and simplify their system architecture.

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The MLOps Blog

APRIL 17, 2023

Such metadata include: Algorithms used. Once you understand your backend architecture, you can also follow domain-driven design principles to build a frontend architecture. Performance metrics and results. Experiment duration. Input dataset. Time the experiment started. Unique identifier for the run.

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AWS Machine Learning Blog

MAY 23, 2023

SageMaker covers the entire MLOps workflow, from collecting to preparing and training the data with built-in high-performance algorithms and sophisticated automated ML (AutoML) experiments so that companies can choose specific models that fit their business priorities and preferences.

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